Abstract:

An endmember detection and spectral unmixing algorithm that uses both spatial and spectral information is presented. This method, Spatial Piece-wise Convex Multiple Model Endmember Detection (Spatial P-COMMEND), autonomously estimates multiple sets of endmembers and performs spectral unmixing for input hyperspectral data. Spatial P-COMMEND does not restrict the estimated endmembers to define a single convex region during spectral unmixing. Instead, a piece-wise convex representation is used that can effectively represent non-convex hyperspectral data. Spatial P-COMMEND drives neighboring pixels to be unmixed by the same set of endmembers encouraging spatially-smooth unmixing results.

Links:

Citation:

 A. Zare, O. Bchir, H. Frigui, and P. Gader, “Spatially-smooth piece-wise convex endmember detection,” in 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2010. 

@InProceedings{zare2010spatially,
Title = {Spatially-smooth piece-wise convex endmember detection},
Author = {Alina Zare and Ouiem Bchir and Hichem Frigui and Paul Gader},
Booktitle = {2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
Year = {2010},
Month = {June},
Doi = {10.1109/WHISPERS.2010.5594897},
}